Beamforming apparatus and method based on long-term properties of sources of undesired noise affecting voice quality

ABSTRACT

A beamforming technique for a microphone array is described to attenuate a source of undesired noise that is deemed the most limiting to audio quality in an acoustic environment. Possible sources of undesired noise include echo, background noise (stationary) and other interference signals (non-stationary). The beamforming technique is updated based on long-term evaluations. Once an evaluation occurs and a decision is made, the beamformer adapts with a maximum responsiveness and without intentional delay, and therefore not affecting the beamformer&#39;s tracking ability. When fixed beamforming is utilized, one of several fixed beamformers having different attenuation targets are selected to implement noise attenuation. When adaptive beamforming is utilized, the beamformer adapts whenever the selected target is deemed dominant.

CROSS-REFERENCED TO RELATED APPLICATIONS

This patent application claims the benefit of U.S. Provisional PatentApplication No. 61/522,517, filed Aug. 11, 2011, entitled, “Beam-FormingMethod Based on Long-Term Properties of Sources of Undesired NoiseAffecting Voice Quality,” which is incorporated herein by reference inits entirety.

FIELD OF THE INVENTION

The invention relates generally to the field of digital signalprocessing for acoustic applications, and more particularly to improvedmicrophone beamforming strategies based on long-term properties ofsources of undesired noise to improve voice quality in an acousticenvironment.

BACKGROUND OF THE INVENTION

The desire for hands-free communications (e.g. cell phones, smartphones, etc.) has led to the increased use of microphone arrays incommunications devices. A microphone array that is configured with known“beamforming” techniques can create an acoustic null directed towardundesired noise and therefore attenuate the noise relative to desiredsound or speech being captured by the microphone array. Such beamformerscan be fixed or adaptive as discussed below.

There are generally three main sources of undesired noise that affectvoice quality: echo from speakers that are associated with thecommunications device, local noise (background noise), and interference(stationary or non-stationary voice such as competing speech).Typically, the choice regarding what source of undesired noise toattenuate is pre-selected by a user or manufacturer. In doing so,various factors are considered including: acoustics of the device,microphone acoustics, and known information about the most disruptivesource of undesired noise. For example, if fixed beamformers are beingutilized and the user makes the predetermined decision that echo shouldbe attenuated, then the appropriate beamformer geared towards echoattenuation is activated, and the other fixed beamformers aredeactivated.

With adaptive beamforming, the noise targeted for attenuation is alsopre-selected so that adaptive beamforming becomes active when thetargeted noise is dominant over the other noise sources. Compared tofixed beamformers, an adaptive beamformer can directionally steer thenull in the reception pattern of the microphone array in real time tofollow any movement of the targeted noise source. For example, assuminginterference is pre-selected, and if a competing speaker's voice ispresent, then attenuation would be applied whenever the competingspeaker's voice (interference) is dominant as compared to echo andnoise. The interference would continue to be attenuated using adaptivebeamforming even as the competing speaker changes positions relative tothe microphone array. However, since the decision of which noise totarget is typically pre-selected, the user may not be aware of the noisesource that will be most disturbing to sound quality at the time thedecision is made.

Another approach is to attenuate the dominant source of undesired noiseat any given time without any pre-selection. The dominant noise sourceis detected and a null is steered towards the recognized dominant sourcein a continuous real-time manner, regardless of noise type. Echo isoften the noise that is dominant the majority of the time, except duringperiods of intermittent noise and/or interference activity thatovershadows the echo. The drawback with this approach is that theadaptive beamformer is constantly “chasing” or “adapting to” a differenttarget, which negatively effects the convergence time of the beamformerand the overall echo cancellation because echo is very dynamic in termsof direction and amplitude. One method to mitigate chasing is to slowdown the adaptation of the beamformer. However, if the adaptation isslowed down too much, then the “noise tracking” ability for movinginterference sources is negatively impacted. For example, if local noisebecomes dominant over echo and the source moves relative to themicrophone array, then slowing the adaptation may impede the ability ofthe beamformer to adequately track the moving local noise Ideally, whatis needed but not conventionally available, is for the beamformeradaption to occur quickly and efficiently with regards to attenuatingthe noise source that has the highest impact on degrading the overallsound quality, but does not get distracted or affected easily by othermomentary factors.

BRIEF DESCRIPTION OF THE DRAWINGS/FIGURES

The accompanying drawings are included to provide further understanding,are incorporated in and constitute a part of this specification, andillustrate embodiments that, together with the description, serve toexplain the principles of the invention. In the drawings:

FIG. 1 illustrates an exemplary block diagram of a noise reductiondevice according to an embodiment of the present invention.

FIG. 2 is a flowchart illustrating the processes conducted within aNoise Evaluation Module according to an exemplary embodiment of thepresent invention.

FIG. 3 illustrates a block diagram that includes certain aspects of aNoise Evaluation Module according to an exemplary embodiment of thepresent invention.

FIG. 4 illustrates a block diagram that includes a Beamfomer ApplicationModule according to an exemplary embodiment of the present invention.

FIG. 5 illustrates a block diagram that includes another BeamfomerApplication Module according to an exemplary embodiment of the presentinvention.

FIG. 6 illustrates block diagram of a noise reduction device accordingto another embodiment of the present invention.

The present invention will now be described with reference to theaccompanying drawings. In the drawings, like reference numbers indicateidentical or functionally similar elements. Additionally, the left-mostdigit(s) of a reference number identifies the drawing in which thereference number first appears.

DETAILED DESCRIPTION

In the following description, numerous specific details are set forth inorder to provide a thorough understanding of the invention. However, itwill be apparent to those skilled in the art that the invention,including structures, systems, and methods, may be practiced withoutthese specific details. The description and representation herein arethe common means used by those experienced or skilled in the art to mosteffectively convey the substance of their work to others skilled in theart. In other instances, well-known methods, procedures, components, andcircuitry have not been described in detail to avoid unnecessarilyobscuring aspects of the invention.

References in the specification to “one embodiment,” “an embodiment,”“an example embodiment,” etc., indicate that the embodiment describedmay include a particular feature, structure, or characteristic, butevery embodiment may not necessarily include the particular feature,structure, or characteristic. Moreover, such phrases are not necessarilyreferring to the same embodiment. Further, when a particular feature,structure, or characteristic is described in connection with anembodiment, it is submitted that it is within the knowledge of oneskilled in the art to effect such feature, structure, or characteristicin connection with other embodiments whether or not explicitlydescribed.

FIG. 1 illustrates an exemplary block diagram of a Noise ReductionDevice 100 according to an embodiment of the present invention. Amicrophone array 101 captures analog signals from a source of desiredsound 102 and a plurality of sources of undesired noise including echo103, interference 104, and noise 105. The microphones in the microphonearray 101 may be a plurality of omnidirectional microphones. The echo103 is the feedback from a speaker 106 that is associated with themicrophone array 101. The device 100 may be present in VoIP tablets, IPphones, WiFi phones, Cell phones (hands-free), set top boxes (withVoIP), Skype TV accessories, gaming platforms with interactive audiocapability (VoIP), or other similar devices.

The Noise Reduction Device 100 further contains a Received SignalProcessing Module 109 to process a received signal 110 that is meant forbroadcast by speaker 106, which inadvertently generates the echo 103.Accordingly, the received signal 110 may be a digital signalrepresenting the voice of another speaker on a phone call that is to bebroadcast by speaker 106 of the device 100.

Codecs 117 coupled to the output of each microphone in the microphonearray 101, convert the received analog signals into digital signals 118.The digital signals 118 are provided to an Echo Cancellation Module 111to cancel echo 103 caused by the received signal 110, since receivedsignal 110 is known. More specifically, received signal processingmodule 109 generates a digital version of received signal 110 that issent to Echo Cancellation Module 111, where it is filtered using filters125 to account for room acoustics. In an embodiment, the EchoCancellation Module 111 may be configured to cancel echo in multiplechannels. Echo cancellation module 111 then cancels the filtered versionof the received signal 110 from the digital signals 118 and outputsecho-cancelled signals 113. The echo-cancelled signals 113 having thedesired sound and undesired noise are provided to a Noise EvaluationModule 107 and to a Beamformer Application Module 108 within a processor120 or a similar environment. It is noted that the undesired noise caninclude residual echo that still exits after echo cancellation due toimperfect echo cancellation, and therefore will be considered by theNoise Evaluation Module 107 as a possible target source. Processor 120may be a digital signal processor (“DSP”), for example, operatingvarious hardware and or software signal processing modules as describedherein.

The Noise Evaluation Module 107 picks which undesired noise source toattenuate, and generates attenuation information 116 to identify thetarget noise source. This attenuation information 116 is then providedto the Beamformer Application Module 108 to implement the attenuationdecision made in the Noise Evaluation Module 107. More specifically, theBeamformer Application Module 108 attenuates the data representative ofthe targeted noise identified by attenuation information 616, togenerate attenuated signals 119. The attenuation can be implemented withany multi-microphone technique that is capable of attenuating datarepresentative of sound received from a predefined direction relative tothe microphone array, including but not limited to steering a null inthe target direction.

Still referring to FIG. 1, a Post Processing Module 121 is included aswell. After attenuation occurs in the Beamformer Application Module 108,the attenuated signals 119 are forwarded to the Post Processing Module121 for any post processing that may be done, as will be understood byone of ordinary skill in the art.

FIG. 2 is a flowchart illustrating the processes conducted within aNoise Evaluation Module 107 according to an exemplary embodiment of thepresent invention. In step 202, the Noise Evaluation Module 107 receivesa plurality of echo-cancelled digital signals from the Echo CancellationModule 111 based on the digital signals received from the array ofmicrophones 101. In step 204, the information in the signals isdifferentiated as belonging to either desired sound 102 or to a type ofundesired noise, such as echo 103, interference 104, or noise 105. Instep 206, noise evaluation module 107 estimates a level of annoyance foreach type of the undesired noises to determine the relative impact onsound quality of the microphone array 101. For example, the level ofannoyance may be the individual decibel levels of the different types ofnoise. This level of annoyance is not calculated at an instantaneousmoment, but rather over a longer time period. In one embodiment, theperiod is in the order of seconds, and can include individuallyaveraging the respective noise sources over a predetermined period oftime. For each of the estimates, other factors, such as echocancellation information from the Echo Cancellation Module 111, may betaken into account to estimate the level of annoyance. In step 208, thelevels of annoyance are then utilized within decision logic to choosewhich type of undesired noise should be attenuated to best improve soundquality of the microphone array 101.

Detection of desired sound may be based on pre-defined conditions. Thisis especially important when there may be similar sources of desiredsound and undesired noise. For example, where one speaker's voice isdesired sound and a competing speaker's voice represents the undesirednoise. The pre-defined conditions may include an expectation that anysound from a certain angle relative to the microphone array, in front ofthe array, or any other particular formulation is a desired sound. Insuch a case when a voice of a speaker in front of a device is considereddesired sound, another speaker's voice from the side of the device wouldbe treated as interference, and thus undesired noise. Alternatively,desired sound can be designated using speaker identification, and aparticular individual's voice can be tracked even if the person ismoving in the local environment, or the device is a hand-held and ismoving relative to the interference.

The application of the decision logic may be a function of numerousvariables. For example, if one source dominates another source by acertain amount of decibels (i.e. signal strength) for a certain periodof a time, then that particular source would be chosen as the targetnoise source to be attenuated. For example, if echo 103 dominates noise105 and/or interference 104 by 3 db for two seconds, or echo 103dominates noise 105 and/or interference 104 by 2 db for three seconds,then echo is selected to be the noise target that is to be attenuated bythe beamformers in the Noise Reduction Module 108. In other embodiments,the desired sound can serve as a common reference or each type of thecaptured undesired noise can be compared with each other, or apre-defined reference point. Furthermore, numerous linear and non-linearvariations of the decision logic can be implemented.

The advantage of estimating levels of annoyance based on a longer timeperiod rather than an instantaneous moment is that the noise sourcetargeted for attenuation will not continuously vary based oninstantaneous (noise-like) changes in the environment. Therefore, if asilent noise source suddenly becomes momentarily active, it would beundesirable for the device to start targeting that source when it isonly active for an instantaneous moment. For example, if the echo 103 isconstantly dominant and a competing source speaks (interference 104) ormakes a noise 105, a user would not want to adapt the beamformingtowards that competing source as the person may be quiet after sayingone word at a high decibel level. If the beamforming were to be adaptedtowards that source, the echo 103 will not be addressed and thereforeaffect the overall voice quality that is produced by the microphone. Asa further example, a door slam should not steer away the beamformingfrom the primary source of undesired noise. Accordingly, the long-termestimate of the level of the annoyance of all three undesired sources inthe present invention allows for more sophisticated use of attenuationfor higher voice quality. Essentially, it is desired to take intoaccount a threshold loudness for a threshold period of time during thesteps 206 and 208.

FIG. 3 illustrates a Block Diagram 300 which further defines NoiseEvaluation Module 107 in accordance with an exemplary embodiment of thepresent invention. FIG. 3 is illustrative of undesired noise levelestimation and application of decision logic by the Decision LogicModule 301 and the factors that may impact estimations of levels ofannoyance. FIG. 3 purposefully does not illustrate the use andapplication of desired sound in order to better focus on comprehensionof the levels of annoyance estimation process that is associated witheach type of undesired noise.

Still referring to FIG. 3, Echo canceller information 115 is providedfrom the Echo Cancellation Module 111, received signal processing info112 is provided from the Received Signal Processing Module 109 andecho-cancelled signals 113 are provided from the Echo CancellationModule 111. The Echo Level Estimation Module 302 estimates the level ofannoyance of the echo 103. For this estimation, the Echo LevelEstimation Module 302 takes into account the echo-cancelled signals 113,but it may also use echo canceller information 115 to estimate theoverall effect of the echo 103. In an embodiment, quantities utilized tomeasure the level of annoyance for the echo 103 may include quantitiessuch as Echo Return Loss or Echo Return Loss Enhancement. As discussedpreviously, an estimation of the level of annoyance is not based just ona particular instantaneous moment but over a long-term period in theorder of seconds, and may include averaging one or more parametersrelated to particular noise over the designated time period.Additionally, the received signal processing info 112 or otherinformation can be taken into account for a more accurate estimation ofthe level of annoyance. Similar to the Echo Level Estimation Module 302,the Noise Level Estimation Module 303 and the Interference LevelEstimation Module 304 observe the digital signals and estimate thelevels of annoyance for their respective noise sources on a relativelylong-term basis, as opposed to an instantaneous decision. Furthermore,similarly to the Echo Level Estimation Module 302, other relevantinformation can be provided to the Noise Level Estimation Module 303 andthe Interference Level Estimation Module 304 for a more accurateestimation of the levels of annoyance.

In an another embodiment of the Noise Evaluation Module 107, both echo103 and noise 105 may first be evaluated to detect if they should beattenuated. If both echo 103 and noise 105 are present, then anevaluation is done with regards to which of the two sources is dominant.If only one of echo 103 and noise 105 is present, then that type ofundesired noise would be attenuated. Furthermore, if neither of thetypes of undesired sources are present, then any other sources of noiseare evaluated to see if they are desired sound 102 (e.g., desired sourcespeaking) or interference 104 (e.g. competing speech). In this case, ifboth a desired sound 102 and interference 104 are detected, theninterference 104 would be attenuated. However, it is imperative whenevaluating the level of annoyance that the evaluation is done on along-term basis. In an exemplary embodiment, a long-term timeframe wouldbe in the order of seconds and not instantaneous, and may includeaveraging over the selected time period.

FIG. 4 illustrates a Block Diagram 400 which further defines BeamformerApplication Module 108 according to an exemplary embodiment of thepresent invention. In this embodiment, an adaptive beamformer 401 isutilized. When the Noise Evaluation Module 107 chooses an undesirednoise source to attenuate, the adaptive beamformer 401 implements thebeamforming to attenuate the targeted noise by effectively attenuatingdata in the reception pattern of the microphone array in the directionof the targeted noise source, using known beamforming techniques. Morespecifically, the echo-cancelled signals 113 are processed so that datarepresentative of sound from the direction of targeted noise isattenuated relative to sound from other directions. For example, if theNoise Evaluation Module 107 identifies noise 105 as the target, then theadaptive beamformer 401 tracks the noise 105 and attenuates the datarepresentative of sound received in the direction of the targeted noise,which can include but is not limited to null steering in the directionof the targeted noise. The speed of the adaptation occurs at its mostresponsive rate to maximize tracking ability of a moving noise source,as opposed to a reduced rate that would occur if an intentional delaywas introduced.

The advantage of the present invention is that the impact of the noisesources on acoustic quality are examined over a relative long period oftime (e.g. seconds) prior to picking the noise target to attenuate. Thisprecludes continuously “chasing” a noise source(s) that is high strengthbut short in duration (e.g. a door slam, or intermittent speaker).However, once the noise target is determined then the adaptation occursat the maximum responsiveness (e.g. instantaneous), without anyintentional delay introduced. This will maximize noise tracking abilityof a moving noise source.

FIG. 5 further illustrates Block Diagram 500 that further defines aBeamformer Application Module 108 according to another exemplaryembodiment of the present invention. In this embodiment, fixedbeamformers are utilized. Each beamformer is configured to attenuate aparticular characteristic. For example, beamformer 501 may be configuredto attenuate echo 103, beamformer 502 may be configured to attenuatenoise 105, and beamformer 503 may be configured to attenuateinterference 104. If the Noise Evaluation Module 107 determines thatnoise 105 is dominant and should be attenuated, then beamformer 502would be selected to directionally attenuate noise 105. For example in afixed beamforming environment, one beamformer would be chosen toattenuate the echo 103, while another one would be chosen to attenuateinterference 104 from the sides of the microphone. The presentembodiment may be modified to further contain a plurality of additionalfixed beamformers, as will be understood by those skilled in the arts.

FIG. 6 illustrates a block diagram of a Noise Reduction Device 600according to another embodiment of the present invention. A microphonearray 601 captures analog signals from a source of desired sound 102 anda plurality of sources of undesired noise including echo 603,interference 604, and noise 605. The microphones in the microphone array601 may be a plurality of omnidirectional microphones. The device 600may operate in a similar environment as device 100. The echo 603 is thefeedback from a speaker 606 that is associated with the microphone array601. Codecs 617 coupled to the output of microphone array 601, convertthe received analog signals into digital signals 613. The digitalsignals 613 having the desired sound and undesired noise are provided toa Noise Evaluation Module 607 and to a Beamformer Application Module 608within a processor 620 or a similar environment. Processor 620 may be adigital signal processor (“DSP”), for example, operating varioushardware and or software signal processing modules as described herein.

The Noise Evaluation Module 607 picks which undesired noise source toattenuate, and generates attenuation information 616 to identify thetarget noise source. This attenuation information 616 is then providedto the Beamformer Application Module 608 to implement the attenuationdecision made in the Noise Evaluation Module 607. More specifically, theBeamformer Application Module 608 attenuates the data representative ofthe targeted noise identified by attenuation information 616, togenerate attenuated signals 614. The Noise Reduction Device 600 furthercontains a Received Signal Processing Module 609 to process a receivedsignal 610 that is meant for broadcast by speaker 606, whichinadvertently generates the echo 603. Accordingly, the received signal610 may be a digital signal representing the voice of another speaker ona phone call that is to be broadcast by speaker 606 of the device 600.

Still referring to FIG. 6, an Echo-Cancellation Module 611 and PostProcessing Module 612 are included as well. After attenuation occurs inthe Beamformer Application Module 608, the attenuated signals 614 arepassed to the Echo Cancellation Module 611, to cancel echo 603 caused bythe received signal 610, since received signal 610 is known. Morespecifically, received signal processing module 609 generates a digitalversion of received signal 610 that is sent to echo cancellation module611, where it is filtered by filter 625 to account for room acoustics.Echo Cancellation Module 611 then cancels the filtered version of thereceived signal 610 from the outputted attenuation signals 614 from theBeamformer Application Module 608. After echo cancellation, the combinedsignals are forwarded to the Post Processing Module 612 for any postprocessing that may be done, as will be understood by one of ordinaryskill in the art.

Still referring to FIG. 6, the Noise Evaluation Module 607 andBeamformer Application Module 608 may function similarly to therespective Noise Evaluation Module 107 and Beamformer Application Module108 of the exemplary embodiment presented in FIG. 1. Digital signals613, received signal processing info 612, echo canceller info 615,attenuation information 616 and attenuated signals 614 provide similarfunctionality within the respective modules as echo-cancelled signals113, received signal processing info 112, echo canceller info 115,attenuation information 116 and attenuated signals 114 respectively.

By comparison to system 100, instead of echo-cancelled signals 113 beingprovided to the Noise Evaluation Module 107 and Beamformer ApplicationModule 108, in the system 600, digital signals 613 are provided directlyfrom the output of the codecs 617 coupled to the array of themicrophones 601. Therefore, system 600 performs the beamforming prior toecho cancellation, whereas system 100 performs these functions in thereverse order.

However, the determination of levels of annoyance within a respectiveNoise Evaluation Module 607 and the application of the beamformers inthe Beamformer Application Module 608 are conducted in analogousmanners.

Other Modifications

In another exemplary embodiment, for choosing the type of undesirednoise to attenuate after the application of decision logic in the NoiseEvaluation Module 107, a soft decision is made with respect to thedecision logic. In this exemplary embodiment, instead of extending fullattenuation towards only one source of a type of undesired noise by thebeamformer, a weighted summation is calculated, and this calculation isutilized to attenuate a plurality of sources of undesired noise.

In another exemplary embodiment, a feedback loop can be provided fromthe Beamformer Application Module 108 to the Noise Evaluation Module107. This could be utilized both for a hard decision extendingattenuation towards only one source of undesired noise or a softdecision extending attenuation towards a plurality of sources ofundesired noise. This feedback loop would allow the Decision LogicModule 301 to take into account the effect of the beamformers.Accordingly, for the selection in Step 208 of FIG. 2, the NoiseEvaluation Module 107 would not be limited to considering only thedigital signals 113 for the microphone levels, but also the impact onthe digital signals 113 of attenuation post the respective beamformers.For example, one of these beamformers which may attenuate onecharacteristic may amplify another characteristic, having an overallnegative impact on voice quality. Thus, it would be helpful to use thesesignals in annoyance level checks not only for the microphone signalsbut also the post-beamforming signals to make a decision based onoverall impact for the improvement of voice quality.

In another exemplary embodiment, an evaluation may be done regarding theexpected performance of the beamformers in a respective BeamformerApplication Module with respect to attenuation of any undesired noise.This expected performance information may be considered by the NoiseEvaluation Module when making the selection as to which one of theplurality of types of noise to attenuate. In other words, the purpose isto avoid selecting noise sources for attenuation that have a lowprobability for success. Therefore, an estimation can be made as tolikely success in attenuating a particular noise source(s), and theestimate can used during the decision of which noise source to target.

The representative signal processing functions described herein (e.g.noise evaluation, fixed and adaptive beamforming, echo cancellation,etc.) can be implemented in hardware, software, or some combinationthereof. For instance, the signal processing functions can beimplemented using computer processors, computer logic, applicationspecific circuits (ASIC), digital logic, digital signal processors,etc., as will be understood by those skilled in the arts based on thediscussion given herein. Accordingly, any processor that performs thesignal processing functions, or logic selection, described herein iswithin the scope and spirit of the present invention.

Further, the signal processing functions described herein could beembodied by computer program instructions that are executed by acomputer processor or any one of the hardware devices listed above. Thecomputer program instructions cause the processor to perform the signalprocessing functions described herein. The computer program instructions(e.g. software) can be stored in a computer usable medium, computerprogram medium, or any storage medium that can be accessed by a computeror processor. Such media include a memory device such as a RAM or ROM,or other type of computer storage medium such as a computer disk or CDROM, or the equivalent. Accordingly, any computer storage medium havingcomputer program code that cause a processor to perform the signalprocessing functions described herein are within the scope and spirit ofthe present invention.

CONCLUSION

It is to be appreciated that the Detailed Description section, and notthe Abstract section, is intended to be used to interpret the claims.The Abstract section may set forth one or more but not all exemplaryembodiments of the present invention as contemplated by the inventors,and thus, is not intended to limit the present invention and theappended claims in any way.

The present invention has been described above with the aid offunctional building blocks illustrating the implementation of specifiedfunctions and relationships thereof. The boundaries of these functionalbuilding blocks have been arbitrarily defined herein for the convenienceof the description. Alternate boundaries can be defined so long as thespecified functions and relationships thereof are appropriatelyperformed.

The foregoing description of the specific embodiments will so fullyreveal the general nature of the invention that others can, by applyingknowledge within the skill of the art, readily modify and/or adapt forvarious applications such specific embodiments, without undueexperimentation, without departing from the general concept of thepresent invention. Therefore, such adaptations and modifications areintended to be within the meaning and range of equivalents of thedisclosed embodiments, based on the teaching and guidance presentedherein. It is to be understood that the phraseology or terminologyherein is for the purpose of description and not of limitation, suchthat the terminology or phraseology of the present specification is tobe interpreted by the skilled artisan in light of the teachings andguidance.

The breadth and scope of the present invention should not be limited byany of the above-described exemplary embodiments, but should be definedonly in accordance with the following claims and their equivalents.

1. A noise-reduction device, comprising: a microphone array; at leastone codec configured to convert analog signals from the microphone arrayinto digital signals; a processor, configured to: receive the digitalsignals from the at least one codec; apply echo cancellation to thereceived digital signals to produce echo-cancelled signals; detectdesired sound and a plurality of types of noise in the echo-cancelledsignals; determine a level of annoyance over a threshold period of timefor each of the plurality of types of noise; select one of the pluralityof types of noise to attenuate based on the determined levels ofannoyance and using pre-defined decision logic; and apply a beamformingtechnique to the digital signals to attenuate the selected noise type.2. The noise-reduction device of claim 1, wherein the threshold periodof time is in the order of seconds.
 3. The noise-reduction device ofclaim 1, wherein the plurality of types of noise comprise two or more ofecho, interference, and local noise.
 4. The noise-reduction device ofclaim 3, wherein the desired sound is pre-defined based on one of: aspatial relationship relative to the microphone array, or speakeridentification.
 5. The noise-reduction device of claim 1, wherein theprocessor is further configured to apply the beamforming techniqueutilizing a plurality of fixed beamformers, and wherein each of theplurality of fixed beamformers is configured to attenuate a particularacoustic characteristic.
 6. The noise-reduction device of claim 1,wherein the processor is further configured to apply the beamformingtechnique utilizing an adaptive beamformer to adapt to the selected typeof noise.
 7. The noise-reduction device of claim 1, wherein the decisionlogic is based on a linear function between the level of annoyance foreach of the plurality of types of noise and the threshold period oftime.
 8. The noise-reduction device of claim 1, whereinecho-cancellation information is used in determination of the level ofannoyance for each of the plurality of types of noise.
 9. Thenoise-reduction device of claim 8, where noise-repression information isfurther used in determination of the level of annoyance for each of theplurality of types of noise.
 10. A noise-reduction device, comprising: amicrophone array; a codec configured to convert analog signals from themicrophone array to digital signals; a processor, configured to: receivedigital signals from the codec; detect from the digital signals aplurality of sources comprising desired sound, echo, interference andnoise; determine a level of annoyance of echo, interference and noise;choose one of echo, interference and noise to attenuate based on thedetermined levels of annoyance over a threshold period of time in theorder of seconds and application of pre-defined decision logic; andapply a beamforming technique instantaneously based on the choice.
 11. Amethod for improving audio quality in a communication device,comprising: receiving digital signals based on analog signals capturedby a microphone array; detecting desired sound and a plurality of typesof noise from the received digital signals; determining a level ofannoyance over a threshold period of time for each of the plurality oftypes of noise; selecting one of the plurality of types of noise toattenuate based on the determined levels of annoyance and application ofpre-defined decision logic; and applying a beamforming technique to thedigital signals to attenuate the selected noise type.
 12. The method ofclaim 11, wherein the threshold period of time is in the order ofseconds.
 13. The method of claim 11, wherein the plurality of types ofnoise comprise two or more of echo, interference and noise.
 14. Themethod of claim 13, wherein the desired sound is pre-defined based onone of: a spatial relationship relative to the microphone array, orspeaker identification on spatial properties or speaker identification.15. The method of claim 11, wherein applying the beamforming techniqueincludes the use of a plurality of fixed beamformers, and wherein eachof the plurality of fixed beamformers attenuates a particular acousticcharacteristic.
 16. The method of claim 11, wherein applying thebeamforming technique includes the use of an adaptive beamformer toadapt to the selected one of the plurality of types of noise.
 17. Themethod of claim 11, wherein the decision logic is based on a linearfunction between the level of annoyance for each of the plurality oftypes of undesired noise and the threshold period of time.
 18. Themethod of claim 11, wherein echo-cancellation information is used indetermining the level of annoyance for each of the plurality of types ofnoise.
 19. The method of claim 18, wherein noise-repression informationis further used in determining the level of annoyance for each of theplurality of types of undesired noise.